Hypothesis Testing Errors
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Objective
I can differentiate between Type I and Type II errors in hypothesis testing.
Part 1 of 4
Warm-up video
jbstatistics · 8:11
We don't generate video — this one is by jbstatistics on YouTube. The practice questions and exit ticket below were drafted by AI for this objective, and every question is editable in the teacher guide.
Part 2 of 4
Key concepts
3 concepts
- 1
A Type I error occurs when the null hypothesis is rejected when it is actually true, whereas a Type II error occurs when the null hypothesis is not rejected when it is actually false.
- 2
The probability of making a Type I error is denoted by alpha, while the probability of making a Type II error is denoted by beta.
- 3
The power of a test is the probability of rejecting the null hypothesis when it is false, and it is calculated as 1 - beta.
Part 3 of 4
Practice
12 questions
What type of error occurs when you reject the null hypothesis, but the null hypothesis is actually true?
Define a Type II error in the context of hypothesis testing.
Part 4 of 4
Exit ticket
Quick comprehension check
“Explain the difference between a Type I error and a Type II error in hypothesis testing. Provide an example of each in the context of testing whether the average height of adult women is 5'4".”
Sample answer included in the free materials
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Teacher Guide
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